Computer-implemented lending analysis systems and methods

• US 20070050286A1
• Filed: 08/26/2005
• Published: 03/01/2007
• Est. Priority Date: 08/26/2005
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Zhang, Mingyuan, Abrahams, Clark
• Granted Patent: US 7,805,345 B2
• Time in Patent Office: Days
• US Class Current: 705/38
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

In accordance with the teachings described herein, computer-implemented lending analysis systems and methods are provided. A pre-processing module may be used to organize loan applicant data into a plurality of applicant groups based on one or more demographic factors, wherein a protected class is identified from the plurality of applicant groups. An index generation module may be used to calculate a plurality of disparity indices for the protected class by comparing lending-related data for the protected class with lending-related data for one or more control groups selected from the applicant groups. An indicator generation module may be used to calculate one or more singular indicators for the protected class by comparing the disparity indices with one or more reference indices. The indicator generation module may be further used to calculate a global indicator as a function of a plurality of singular indicators.

Claims

1. A computer-implemented method for analyzing lending data, comprising:

processing loan applicant data into a plurality of applicant groups based on one or more demographic factors;

wherein a protected class is identified from the plurality of applicant groups;

calculating a plurality of disparity indices for the protected class by comparing lending-related data for the protected class with lending-related data for one or more control groups selected from the applicant groups; and

calculating one or more singular indicators for the protected class by comparing the disparity indices with one or more reference indices.

2. The method of claim 1, wherein a plurality of singular indicators are calculated, further comprising:

calculating a global indicator as a function of the plurality of singular indicators.

3. The method of claim 2, wherein the global indictor is calculated using a Euclidean distance formula.

4. The method of claim 2, wherein the global indictor is calculated as a weighted average of the plurality of singular indicators.

5. The method of claim 1, wherein a reference index is calculated for each of the plurality of disparity indices.

6. The method of claim 1, wherein the one or more demographic factors include at least one of race, geographic location, gender, income level, color, ethnicity, religion, national origin, marital status, handicap, disability, familial status, age, or receipt of public assistance income.

7. The method of claim 1, wherein the one or more singular indicators are calculated using a distance analysis technique.

8. The method of claim 7, further comprising:

determining linear coefficients for the disparity indices and the reference indices, wherein the one or more singular indicators are calculated as a difference measure between the linear coefficients for the reference indices and the linear coefficients for the disparity indices.

9. The method of claim 8, wherein the linear coefficients are calculated using a multivariate analysis to represent the indices with principal components.

10. The method of claim 9, wherein the one or more singular indicators are Mehalanobis distance measures.

11. The method of claim 1, wherein the reference indices are calculated using pre-defined criteria.

12. The method of claim 1, wherein the reference indices are calculated using peer or industrial composite data.

13. The method of claim 1, wherein the reference indices are calculated by assuming a value of 1.0 for one or more of the disparity indices.

14. The method of claim 1, wherein the reference indices are calculated using average values for one or more of the disparity indices.

15. The method of claim 1, wherein the reference indices are determined using average values for one or more of the disparity indices across a plurality of lending institutions.

16. The method of claim 1, wherein the reference indices are calculated by assuming a maximum or minimum value for one or more of the disparity indices.

17. The method of claim 1, wherein the reference indices are calculated using simulations.

18. The method of claim 1, wherein the reference indices are determined based upon at least one of an institution'"'"'s current goal or strategic plan, regulatory guidance, historical performance, and a peer composite.

19. The method of claim 1, further comprising:

prior to the step of processing loan applicant data, merging the loan applicant data from two or more databases into a plurality of applicant records.

20. The method of claim 1, further comprising:

validating the loan applicant data in one or more of the applicant groups to determine if one or more data fields are missing or outside of an expected range.

21. The method of claim 20, further comprising:

replacing data fields that are missing or outside of the expected range with one or more default values.

22. The method of claim 1, wherein the step of organizing load applicant data includes:

defining a handle to represent an applicant group, wherein the handle is defined based on a plurality of lending-related factors regarding the applicant group.

23. The method of claim 22, wherein the handle is a borrower risk based handle, and wherein the plurality of lending-related factors include at least one of debt-to-income range, loan-to-value ratio range, credit bureau score, and credit history.

24. The method of claim 22, wherein the handle is a transaction based handle, and wherein the plurality of lending-related factors include at least one of pricing option, term to maturity, loan amount tier, and down payment amount.

25. The method of claim 22, wherein the handle is a property-based handle, and wherein the plurality of lending-related factors include at least one of age, type of structure on a property, property location, appraisal method, and flood zone.

26. The method of claim 1, further comprising:

generating a user interface that may be used to display representations of the one or more singular indicators and the plurality of disparity indices.

27. The method of claim 1, wherein at least one of the disparity indices is an origination disparity index, the origination disparity index being a rate of loan origination for the control group relative to a rate of loan origination for the protected class.

28. The method of claim 1, wherein at least one of the disparity indices is a fallout disparity index, the fallout disparity index being a rate of loan fallout for the protected class relative to a rate of loan fallout for the control group.

29. The method of claim 1, wherein at least one of the disparity indices is a market penetration index, wherein the control group represents an entire population of a minority group within a geographically defined area, the protected class represents loan applicants of the minority group within the geographically defined area, and the market penetration index is a population size of the minority group within the geographically defined area relative to a loan application rate of the minority group with the geographically defined area.

30. The method of claim 1, wherein at least one of the disparity indices is a product disparity index, the product disparity index being a rate of granted loans above a set dollar amount for the protected class relative to a rate granted loans above the set dollar amount for the control group.

31. The method of claim 1, wherein at least one of the disparity indices is a sub-prime product application mix disparity index, the sub-prime product application mix disparity index being calculated as a first ratio divided by a second ratio, the first ratio being a proportion of sub-prime loan applicants of the protected class relative to a total number of loan applications for the protected class, the second ratio being a proportion of sub-prime loan applicants of the control group relative to a total number of loan applications for the control group.

32. The method of claim 1, wherein at least one of the disparity indices is a sub-prime product organization mix disparity index, which is calculated as a first ratio divided by a second ratio, the first ratio being a proportion of sub-prime loans granted to the protected class relative to a total number of loans originated by the protective class, the second ratio being a proportion of sub-prime loans granted to the control group relative to a total number of loans originated by the control group.

33. The method of claim 1, wherein at least one of the disparity indices is a loan-to-value disparity index, which is a proportion of loan applicants in the control group having a loan-to-value greater than a predetermined threshold relative to a proportion of loan applicants in the protected class having a loan-to-value greater than the predetermined threshold.

34. The method of claim 1, wherein at least one of the disparity indices is a bureau score disparity index, which is a ratio of loan applicants in the control group that have a FICO bureau score below a predetermined threshold to loan applicant in the protected class that have a FICO bureau score below the predetermined threshold.

35. The method of claim 1, wherein at least one of the disparity indices is an income disparity index, which is a ratio of loan applicants in the control group having an income below a predetermined threshold to loan applicants in the protected class having an income below the predetermined threshold.

36. A computer-implemented system for analyzing lending data, comprising:

data organization software instructions configured to organize loan applicant data into a plurality of applicant groups based on one or more demographic factors, wherein a protected class is identified from the plurality of applicant groups;

index generation software instructions configured to calculate a plurality of disparity indices for the protected class by comparing lending-related data for the protected class with lending-related data for one or more control groups selected from the applicant groups; and

indicator generation software instructions configured to calculate one or more singular indicators for the protected class by comparing the disparity indices with one or more reference indices.

37. The system of claim 36, wherein the indicator generation software instructions calculate a plurality of singular indicators, and is further configured to calculate a global indicator as a function of the plurality of singular indicators.

38. The system of claim 37, wherein the global indicator is calculated using a Euclidean distance formula.

39. The system of claim 37, wherein the global indicator is calculated as a weighted average of the plurality of singular indicators.

40. The system of claim 36, wherein the one or more singular indicators are calculated using a distance analysis technique.

41. The system of claim 40, wherein the indicator generation software instructions are further configured to determine linear coefficients for the disparity indices and the reference indices, wherein the one or more singular indicators are calculated as a difference measure between the linear coefficients for the reference indices and the linear coefficients for the disparity indices.

42. The system of claim 41, wherein the linear coefficients are calculated using a multivariate analysis to represent the indices with principal components.

43. The system of claim 42, wherein the one or more singular indicators are Mehalanobis distance measures.

44. The system of claim 36, wherein the data organization software instructions are further configured to validate the loan applicant data in one or more of the applicant groups to determine if one or more data fields are missing or are outside of an expected range.

45. The system of claim 44, wherein the data organization software instructions are further configured to replace data fields that are missing or outside of an expected range with one or more default values.

46. The system of claim 36, wherein the data organization software instructions are further operable to define a handle to represent an applicant group, wherein the handle is defined based on a plurality of lending-related factors regarding the applicant group.

47. The system of claim 36, further comprising:

data visualization software instructions configured to generate a user interface that may be used to display representations of the one or more singular indicators and the plurality of disparity indices.

48. A system for analyzing lending data, comprising:

means for organizing loan applicant data into a plurality of applicant groups based on one or more demographic factors, wherein a protected class is identified from the plurality of applicant groups;

means for calculating a plurality of disparity indices for the protected class by comparing lending-related data for the protected class with lending-related data for one or more control groups selected from the applicant groups; and

mean for calculating one or more singular indicators for the protected class by comparing the disparity indices with one or more reference indices.

49. The system of claim 48, further comprising:

means for calculating a global indicator as a function of the singular indicators.

50. The system of claim 48, further comprising:

means for generating a user interface that may be used to display representations of the one or more singular indicators and the plurality of disparity indices.